| Title |
Removal of redundant contigs from de novo RNA-Seq assemblies via homology search improves accurate detection of differentially expressed genes
|
|---|---|
| Published in |
BMC Genomics, December 2015
|
| DOI | 10.1186/s12864-015-2247-0 |
| Pubmed ID | |
| Authors |
Hanako Ono, Kazuo Ishii, Toshinori Kozaki, Isao Ogiwara, Motoki Kanekatsu, Tetsuya Yamada |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 20% |
| United States | 1 | 10% |
| Taiwan | 1 | 10% |
| Germany | 1 | 10% |
| France | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 60% |
| Members of the public | 3 | 30% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | <1% |
| Chile | 1 | <1% |
| France | 1 | <1% |
| Czechia | 1 | <1% |
| New Zealand | 1 | <1% |
| Spain | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 120 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 30 | 24% |
| Student > Ph. D. Student | 28 | 22% |
| Student > Master | 16 | 13% |
| Student > Bachelor | 15 | 12% |
| Student > Doctoral Student | 9 | 7% |
| Other | 18 | 14% |
| Unknown | 11 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 72 | 57% |
| Biochemistry, Genetics and Molecular Biology | 28 | 22% |
| Computer Science | 3 | 2% |
| Environmental Science | 2 | 2% |
| Neuroscience | 2 | 2% |
| Other | 3 | 2% |
| Unknown | 17 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 December 2015.
All research outputs
#3,016,858
of 25,837,817 outputs
Outputs from BMC Genomics
#892
of 11,320 outputs
Outputs of similar age
#46,886
of 398,345 outputs
Outputs of similar age from BMC Genomics
#30
of 370 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,320 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 398,345 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 370 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.